Content applications are popularly used to create digital content. Certain content applications are designed to synthesize high resolution images that share the same style with a high resolution style image. In other words, a content application can transfer the artistic style, e.g., visual properties, of the artwork shown in a style image to a synthesized image. For example, the style image can be an image of a work of art, such as an image of the Starry Night painting by Van Gogh. Continuing with this example, the synthesized image can be an image of a scene depicting a cloudy day. The artistic style elements, such as brushes, strokes, and patterns, of the Starry Night painting are used as the style that is transferred to the cloudy day image to create the synthesized high resolution image.
Existing content applications use deep neural networks to synthesize an image with a desired artistic style. Typically, a deep neural network is trained at a particular image resolution. That is, the training images are style images having the particular image resolution. Either, a low image resolution (e.g., 256 pixel resolution in width) or a high image resolution (e.g., 1024 pixel resolution in width) is used in prior art solutions.